Global exponential dissipativity and stabilization of memristor-based recurrent neural networks with time-varying delays

Neural Networks

Volumn 48, Issue , 2013, Pages 158-172

  Guo, Zhenyuan ^a,b   Wang, Jun ^b   Yan, Zheng ^b  

^a HUNAN UNIVERSITY   (China)

^b CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Global exponential dissipativity; Memristor; Neurodynamics; Recurrent neural networks; Stabilization

Indexed keywords

DISSIPATIVITY; LASALLE INVARIANT PRINCIPLE; LINEAR STATE FEEDBACK CONTROL; LYAPUNOV FUNCTIONALS; M-MATRIX; MEMRISTOR; NEURODYNAMICS; TIME-VARYING DELAY;

PASSIVE FILTERS; RECURRENT NEURAL NETWORKS; STABILIZATION; TIME VARYING CONTROL SYSTEMS;

MEMRISTORS;

ARTICLE; CONTROLLED STUDY; EQUILIBRIUM ANALYSIS; FEEDBACK SYSTEM; GLOBAL EXPONENTIAL DISSIPATIVITY; LASALLE INVARIANT PRINCIPLE; LYAPUNOV FUNCTIONAL; M MATRIX THEORY; MATHEMATICAL ANALYSIS; MATHEMATICAL PARAMETERS; NERVE CELL NETWORK; PRIORITY JOURNAL; THEORY;

GLOBAL EXPONENTIAL DISSIPATIVITY; MEMRISTOR; NEURODYNAMICS; RECURRENT NEURAL NETWORKS; STABILIZATION;

ALGORITHMS; LINEAR MODELS; NEURAL NETWORKS (COMPUTER); NEURONS; NONLINEAR DYNAMICS;

EID: 84884236106     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2013.08.002     Document Type: Article

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